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@zachpogrob

@zachpogrob

Obsession beats discipline - go all-in on your craft until you either die or get reborn.

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AI Learning Acceleration Framework

Reusability

A method for rapidly learning new skills by using AI to reverse-engineer examples you admire. Instead of following tutorials, you find great examples and have AI explain exactly how to recreate them.

How It Works

Traditional learning follows a curriculum someone else designed. This method lets your taste guide learning. You find examples you love, screenshot them, and ask AI for specific technical details to recreate them. The learning is driven by inspiration rather than instruction. Implementation happens immediately after understanding.

Components

1

Find designs or examples you genuinely admire

2

Screenshot and feed to AI like Claude or ChatGPT

3

Ask for specific technical details to recreate what you see

4

Implement immediately with the AI guidance

5

Repeat across many examples to build comprehensive skill

When to Use

When learning visual or technical skills where good examples exist. When you have strong taste and can identify quality. When you want to learn faster than traditional methods allow. When tutorials feel slow or irrelevant.

When Not to Use

When the field requires deep theoretical understanding before application. When you cannot identify good examples. When you need foundational knowledge that examples cannot provide.

Anti-Patterns to Avoid

Asking AI to explain things you do not actually want to createLearning in theory without implementing immediatelyChoosing examples based on ease rather than aspirationNot asking follow-up questions when confused

Example

A founder wants to learn Figma to design their app. Instead of taking a course, they screenshot beautiful app interfaces they admire, paste them into Claude, and ask 'What specific Figma settings create this corner rounding and shadow effect?' They implement each answer immediately. In 2 months, they go from zero to designing an entire app.